mirror of
https://github.com/willnorris/imageproxy.git
synced 2026-04-25 21:06:24 +02:00
update all downstream dependencies
no specific features I'm looking to add, just keeping thing up to date. Unit tests and my manual testing seems like everything is still working as expected.
This commit is contained in:
Will Norris
parent
17f19d612f
commit
b5984d2822
25 changed files with 1661 additions and 486 deletions
130
vendor/github.com/disintegration/imaging/resize.go
generated
vendored
130
vendor/github.com/disintegration/imaging/resize.go
generated
vendored
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@ -5,17 +5,12 @@ import (
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"math"
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)
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type iwpair struct {
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i int
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w int32
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type indexWeight struct {
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index int
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weight float64
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}
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type pweights struct {
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iwpairs []iwpair
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wsum int32
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}
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func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights {
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func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) [][]indexWeight {
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du := float64(srcSize) / float64(dstSize)
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scale := du
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if scale < 1.0 {
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@ -23,7 +18,7 @@ func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights {
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}
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ru := math.Ceil(scale * filter.Support)
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out := make([]pweights, dstSize)
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out := make([][]indexWeight, dstSize)
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for v := 0; v < dstSize; v++ {
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fu := (float64(v)+0.5)*du - 0.5
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@ -37,15 +32,19 @@ func precomputeWeights(dstSize, srcSize int, filter ResampleFilter) []pweights {
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endu = srcSize - 1
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}
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wsum := int32(0)
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var sum float64
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for u := startu; u <= endu; u++ {
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w := int32(0xff * filter.Kernel((float64(u)-fu)/scale))
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w := filter.Kernel((float64(u) - fu) / scale)
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if w != 0 {
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wsum += w
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out[v].iwpairs = append(out[v].iwpairs, iwpair{u, w})
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sum += w
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out[v] = append(out[v], indexWeight{index: u, weight: w})
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}
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}
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if sum != 0 {
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for i := range out[v] {
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out[v][i].weight /= sum
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}
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}
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out[v].wsum = wsum
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}
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return out
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@ -127,21 +126,26 @@ func resizeHorizontal(src *image.NRGBA, width int, filter ResampleFilter) *image
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parallel(dstH, func(partStart, partEnd int) {
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for dstY := partStart; dstY < partEnd; dstY++ {
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i0 := dstY * src.Stride
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j0 := dstY * dst.Stride
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for dstX := 0; dstX < dstW; dstX++ {
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var c [4]int32
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for _, iw := range weights[dstX].iwpairs {
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i := dstY*src.Stride + iw.i*4
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c[0] += int32(src.Pix[i+0]) * iw.w
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c[1] += int32(src.Pix[i+1]) * iw.w
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c[2] += int32(src.Pix[i+2]) * iw.w
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c[3] += int32(src.Pix[i+3]) * iw.w
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var r, g, b, a float64
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for _, w := range weights[dstX] {
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i := i0 + w.index*4
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aw := float64(src.Pix[i+3]) * w.weight
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r += float64(src.Pix[i+0]) * aw
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g += float64(src.Pix[i+1]) * aw
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b += float64(src.Pix[i+2]) * aw
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a += aw
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}
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if a != 0 {
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aInv := 1 / a
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j := j0 + dstX*4
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dst.Pix[j+0] = clamp(r * aInv)
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dst.Pix[j+1] = clamp(g * aInv)
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dst.Pix[j+2] = clamp(b * aInv)
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dst.Pix[j+3] = clamp(a)
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}
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j := dstY*dst.Stride + dstX*4
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sum := weights[dstX].wsum
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dst.Pix[j+0] = clampint32(int32(float32(c[0])/float32(sum) + 0.5))
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dst.Pix[j+1] = clampint32(int32(float32(c[1])/float32(sum) + 0.5))
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dst.Pix[j+2] = clampint32(int32(float32(c[2])/float32(sum) + 0.5))
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dst.Pix[j+3] = clampint32(int32(float32(c[3])/float32(sum) + 0.5))
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}
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}
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})
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@ -162,32 +166,33 @@ func resizeVertical(src *image.NRGBA, height int, filter ResampleFilter) *image.
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weights := precomputeWeights(dstH, srcH, filter)
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parallel(dstW, func(partStart, partEnd int) {
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for dstX := partStart; dstX < partEnd; dstX++ {
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for dstY := 0; dstY < dstH; dstY++ {
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var c [4]int32
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for _, iw := range weights[dstY].iwpairs {
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i := iw.i*src.Stride + dstX*4
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c[0] += int32(src.Pix[i+0]) * iw.w
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c[1] += int32(src.Pix[i+1]) * iw.w
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c[2] += int32(src.Pix[i+2]) * iw.w
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c[3] += int32(src.Pix[i+3]) * iw.w
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var r, g, b, a float64
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for _, w := range weights[dstY] {
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i := w.index*src.Stride + dstX*4
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aw := float64(src.Pix[i+3]) * w.weight
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r += float64(src.Pix[i+0]) * aw
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g += float64(src.Pix[i+1]) * aw
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b += float64(src.Pix[i+2]) * aw
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a += aw
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}
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if a != 0 {
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aInv := 1 / a
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j := dstY*dst.Stride + dstX*4
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dst.Pix[j+0] = clamp(r * aInv)
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dst.Pix[j+1] = clamp(g * aInv)
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dst.Pix[j+2] = clamp(b * aInv)
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dst.Pix[j+3] = clamp(a)
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}
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j := dstY*dst.Stride + dstX*4
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sum := weights[dstY].wsum
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dst.Pix[j+0] = clampint32(int32(float32(c[0])/float32(sum) + 0.5))
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dst.Pix[j+1] = clampint32(int32(float32(c[1])/float32(sum) + 0.5))
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dst.Pix[j+2] = clampint32(int32(float32(c[2])/float32(sum) + 0.5))
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dst.Pix[j+3] = clampint32(int32(float32(c[3])/float32(sum) + 0.5))
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}
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}
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})
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return dst
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}
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// fast nearest-neighbor resize, no filtering
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// resizeNearest is a fast nearest-neighbor resize, no filtering.
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func resizeNearest(src *image.NRGBA, width, height int) *image.NRGBA {
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dstW, dstH := width, height
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@ -203,13 +208,16 @@ func resizeNearest(src *image.NRGBA, width, height int) *image.NRGBA {
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parallel(dstH, func(partStart, partEnd int) {
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for dstY := partStart; dstY < partEnd; dstY++ {
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fy := (float64(dstY)+0.5)*dy - 0.5
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srcY := int((float64(dstY) + 0.5) * dy)
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if srcY > srcH-1 {
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srcY = srcH - 1
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}
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for dstX := 0; dstX < dstW; dstX++ {
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fx := (float64(dstX)+0.5)*dx - 0.5
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srcX := int(math.Min(math.Max(math.Floor(fx+0.5), 0.0), float64(srcW)))
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srcY := int(math.Min(math.Max(math.Floor(fy+0.5), 0.0), float64(srcH)))
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srcX := int((float64(dstX) + 0.5) * dx)
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if srcX > srcW-1 {
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srcX = srcW - 1
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}
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srcOff := srcY*src.Stride + srcX*4
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dstOff := dstY*dst.Stride + dstX*4
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@ -324,7 +332,7 @@ func Thumbnail(img image.Image, width, height int, filter ResampleFilter) *image
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return Fill(img, width, height, Center, filter)
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}
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// Resample filter struct. It can be used to make custom filters.
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// ResampleFilter is a resampling filter struct. It can be used to define custom filters.
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//
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// Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali,
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// CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.
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@ -359,7 +367,7 @@ type ResampleFilter struct {
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Kernel func(float64) float64
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}
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// Nearest-neighbor filter, no anti-aliasing.
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// NearestNeighbor is a nearest-neighbor filter (no anti-aliasing).
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var NearestNeighbor ResampleFilter
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// Box filter (averaging pixels).
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@ -371,37 +379,37 @@ var Linear ResampleFilter
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// Hermite cubic spline filter (BC-spline; B=0; C=0).
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var Hermite ResampleFilter
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// Mitchell-Netravali cubic filter (BC-spline; B=1/3; C=1/3).
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// MitchellNetravali is Mitchell-Netravali cubic filter (BC-spline; B=1/3; C=1/3).
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var MitchellNetravali ResampleFilter
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// Catmull-Rom - sharp cubic filter (BC-spline; B=0; C=0.5).
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// CatmullRom is a Catmull-Rom - sharp cubic filter (BC-spline; B=0; C=0.5).
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var CatmullRom ResampleFilter
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// Cubic B-spline - smooth cubic filter (BC-spline; B=1; C=0).
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// BSpline is a smooth cubic filter (BC-spline; B=1; C=0).
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var BSpline ResampleFilter
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// Gaussian Blurring Filter.
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// Gaussian is a Gaussian blurring Filter.
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var Gaussian ResampleFilter
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// Bartlett-windowed sinc filter (3 lobes).
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// Bartlett is a Bartlett-windowed sinc filter (3 lobes).
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var Bartlett ResampleFilter
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// Lanczos filter (3 lobes).
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var Lanczos ResampleFilter
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// Hann-windowed sinc filter (3 lobes).
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// Hann is a Hann-windowed sinc filter (3 lobes).
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var Hann ResampleFilter
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// Hamming-windowed sinc filter (3 lobes).
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// Hamming is a Hamming-windowed sinc filter (3 lobes).
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var Hamming ResampleFilter
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// Blackman-windowed sinc filter (3 lobes).
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// Blackman is a Blackman-windowed sinc filter (3 lobes).
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var Blackman ResampleFilter
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// Welch-windowed sinc filter (parabolic window, 3 lobes).
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// Welch is a Welch-windowed sinc filter (parabolic window, 3 lobes).
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var Welch ResampleFilter
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// Cosine-windowed sinc filter (3 lobes).
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// Cosine is a Cosine-windowed sinc filter (3 lobes).
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var Cosine ResampleFilter
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func bcspline(x, b, c float64) float64 {
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